Achieving high-performance perovskite photovoltaics, especially in ambient air, is critically dependent on the precise optimization of process parameters. However, traditional manual methods often struggle to effectively control the key variables. This inherent challenge requires a paradigm shift toward automated platforms capable of precise and reproducible experiments. Herein, we use a fully automated device acceleration platform (DAP) to optimize air-processed parameters for preparing perovskite devices using a two-step sequential deposition technique. Over ten process parameters with significant potential to influence device performance are systematically optimized. Specifically, we delve into the impact of the dripping speed of organic ammonium halide, a parameter that is difficult to control manually, on both perovskite film and device performance. Through the targeted design of experiments, we reveal that the dripping speed significantly affects device performance primarily by adjusting the residual PbI₂ content in the films. We find that optimal dripping speeds, such as 50 µL s⁻¹, contribute to top-performance devices. Conversely, excessively fast or slow speeds result in devices with comparatively poorer performance and lower reproducibility. The optimized parameter set enables us to establish a standard operation procedure (SOP) for additive-free perovskite processing in ambient conditions, which yield devices with efficiencies surpassing 23%, satisfactory reproducibility, and state-of-the-art photo-thermal stability. This research underscores the importance of understanding the causality of process parameters in enhancing perovskite photovoltaic performance. Furthermore, our study highlights the pivotal role of automated platforms in discovering innovative workflows and accelerating the development of high-performing perovskite photovoltaic technologies.

中文翻译：

---

使用自动化设备加速平台精确控制环境空气中效率 >23% 的钙钛矿太阳能电池的工艺参数


实现高性能钙钛矿光伏发电，尤其是在环境空气中，关键取决于工艺参数的精确优化。然而，传统的手动方法往往难以有效控制关键变量。这一固有的挑战需要向能够进行精确和可重复实验的自动化平台进行范式转变。在这里，我们使用全自动器件加速平台（DAP）来优化空气处理参数，以使用两步顺序沉积技术制备钙钛矿器件。系统优化了十多个对器件性能具有重大影响潜力的工艺参数。具体来说，我们深入研究了有机卤化铵的滴速这一难以手动控制的参数对钙钛矿薄膜和器件性能的影响。通过有针对性的实验设计，我们发现滴速对器件性能的显着影响主要是通过调节薄膜中残留的PbI ₂ 含量来实现的。我们发现最佳滴速（例如 50 µL s ⁻¹ ）有助于实现顶级性能的设备。相反，速度过快或过慢会导致设备性能相对较差且再现性较低。优化的参数集使我们能够建立在环境条件下进行无添加剂钙钛矿加工的标准操作程序 (SOP)，从而生产出效率超过 23%、令人满意的再现性和最先进的光热稳定性的器件。这项研究强调了了解工艺参数的因果关系对于增强钙钛矿光伏性能的重要性。 此外，我们的研究强调了自动化平台在发现创新工作流程和加速高性能钙钛矿光伏技术开发方面的关键作用。